Search Results (49)

Understanding the environmental fate of microplastics (MPs) in agricultural soils remains a major challenge, particularly under field conditions where soil structure and hydraulic processes jointly regulate particle transport and retention. This study investigated whether hydro-physical soil functioning can explain the distribution and accumulation of MPs in pistachio orchard soils from a semi-arid region of southeastern Türkiye. A total of 42 soil samples were analyzed for MP abundance, size distribution, and morphology, together with key hydro-physical properties including texture, porosity, bulk density, aggregate stability, organic matter content, and soil water retention characteristics. To identify the dominant controls on MP occurrence, explainable machine learning approaches combining Random Forest (RF), Gradient Boosting Decision Trees (GBDT), and SHAP (SHapley Additive exPlanations) analysis were employed. Microplastic abundance differed among management systems. Former landfill or construction sites represented the largest proportion of the total recorded microplastic abundance (40.9%), followed by conventionally managed (25.2%), manure-amended (24.5%), and sewage-sludge-amended orchards (9.4%). Median microplastic abundances were 1433, 667, 4633, and 633 particles kg⁻¹ soil, respectively. Fine-sized MPs constituted the dominant particle fraction and exhibited strong associations with pore-system characteristics, indicating that pore-size compatibility governs their retention and mobility within the soil matrix. Morphology-specific analyses further revealed contrasting relationships between soil hydro-physical properties and individual MP forms, suggesting distinct retention pathways for granules, films, fragments, and fibers. Explainable AI analysis identified organic matter, silt content, bulk density, and water retention characteristics as the most influential predictors of MP occurrence. Among the tested models, RF demonstrated superior predictive robustness and generalization capacity. The findings demonstrate that hydro-physical soil functioning plays a central role in determining microplastic fate in agricultural soils and highlight the value of interpretable machine learning frameworks for uncovering the mechanisms underlying contaminant retention and redistribution. Integrating soil structural indicators with explainable artificial intelligence offers a promising pathway for improving microplastic risk assessment in agroecosystems. Full article

The Shangri-La area lies within the Yunnan-Tibet geothermal belt, characterized by intense tectonic activity and abundant geothermal resource potential. However, existing studies have largely focused on individual hot springs, and a regional scale understanding of geothermal geology and fluid circulation mechanisms remains lacking. This study systematically elucidates the geological setting, hydrogeological characteristics, circulation mechanisms, and resource potential of the geothermal systems by integrating hydrogeological surveys with hydro chemical and isotopic analyses. The results indicate that the Zhongxiao Fault Zone and its associated secondary structures are the primary controllers of geothermal water distribution, serving as both thermal conduits and hydrogeological boundaries. The primary heat source is attributed to the natural geothermal gradient, supplemented by additional contributions from magmatic activity. The geothermal waters are classified as Na-HCO₃ or Ca-HCO₃ types and are notably rich in fluoride. The mean values of δD and δ¹⁸O for geothermal water were −127.86‰ and −15.53‰, respectively, exhibiting isotopic depletion compared with non-thermal water. The geothermal water samples plot near both the Global and Local Meteoric Water Lines while exhibiting a distinct mean ¹⁸O shift of +1.24‰, indicating that the systems are recharged by atmospheric precipitation and have subsequently undergone intense water–rock interaction. Analysis using the Na-K-Mg triangle diagram reveals that most geothermal water samples are immature waters. Thus, the quartz geothermometer provides more reliable estimates of reservoir temperatures. Calculations yield reservoir temperatures ranging from 70 °C to 123 °C, characterizing the system as a medium-to-low temperature resource. With an annual exploitable energy of 5.9 × 10¹⁴ J and high fluoride content, these resources can offer substantial potential for clean energy and balneotherapy. Full article

This study presents a computational analysis of degradation caused by cavitation and hydro-abrasive erosion in a low-head axial microturbine ($H=4\mathrm{m}$), incorporating strategic air injection as a passive mitigation technique. Using Computational Fluid Dynamics (CFD) within ANSYS CFX 2025 R2, the study investigates hydrodynamic performance and the spatial distribution of surface wear across the runner blades. The turbine geometry was developed from aerofoil profiles mapped onto cylindrical coordinates, using a structured three-dimensional mesh with localized refinement to ensure grid independence. Physical modeling employed the Shear Stress Transport (SST) turbulence model, with cavitation dynamics governed by the Rayleigh–Plesset equation and sediment transport modeled using a Lagrangian framework incorporating the Finnie erosion model. The numerical framework showed good agreement with reference characteristic curves, confirming its predictive accuracy. The results indicate that vapor cavities form predominantly on the suction side, whereas solid particle erosion highly concentrated on the pressure side of the blades, where the outer $20\%$ of the span accounts for over $91\%$ of the total erosion intensity. Parametric assessments of controlled air injection revealed a highly non-linear mitigation response, identifying IAVF 2 as the optimal air-injection case. This configuration reduced integrated erosion by $0.95\%$ and maximum localized erosion by $6.17\%$. In contrast, excessive air volumes accelerated material removal due to localized flow distortion. The findings indicate that carefully controlled air injection is a viable strategy for extending the operational lifespan of small-scale hydropower assets. Full article

The integration of high-penetration renewable energy creates new requirements for cross-timescale peak shaving and for system robustness under extreme meteorological conditions. This study develops a dual-timescale capacity allocation method for pumped hydro storage (PHS), combining 8760 h chronological production simulation with monthly typical-day retrospective analysis. The model represents the operating limits of conventional units, nuclear power, hydropower, wind power, photovoltaic generation, tie-line exchange, and PHS energy shifting. On this basis, a stepwise capacity-sensitivity framework is established to minimize annualized comprehensive system cost while controlling renewable energy curtailment within a predefined planning threshold, rather than treating zero curtailment as an unconditional monthly hard constraint. Using long-term planning data from a coastal provincial power grid in southeastern China, the study compares the 2035 and 2040 planning scenarios. The results show that isolated typical-day models tend to overestimate PHS requirements because they disconnect chronological continuity and cross-day reservoir buffering. In 2035, the system presents a two-level seasonal capacity structure: 15,000 MW can support normalized operation in stable months, whereas the rigid boundary rises to 19,000 MW under extreme autumn high-wind conditions. In 2040, wind and photovoltaic capacity increase by approximately 20.01 GW compared with 2035, deepening low-net-load valleys and compressing seasonal regulation margins. Under the assumed planning boundary, the recommended PHS capacity converges to 23,000 MW. The proposed framework provides a practical reference for flexible resource planning in coastal power grids with deep renewable energy integration. Full article

Sustainable water resource management in arid and transboundary-dependent regions requires that hydrological assessment be integrated with institutional governance analysis. This study provides a comprehensive hydro-institutional evaluation of water sustainability in Kazakhstan using a multi-source empirical framework. The analysis is based on international and national datasets (FAO AQUASTAT, World Bank, national statistics for 2010–2024) and incorporates key indicators, including per capita renewable water resources, sectoral withdrawal structure, transboundary dependence, and water stress. In addition, a Water Sustainability Composite Index and a Regional Vulnerability Index were developed to capture system-wide sustainability and spatial heterogeneity. The results show that Kazakhstan possesses moderate renewable water availability (approximately 5411 m³ per capita per year), yet exhibits significant structural vulnerability due to high transboundary dependence (40.64%), dominant agricultural water use (≈57%), and infrastructure inefficiencies (25–35% losses). Regional analysis reveals substantial disparities, with southern irrigation-dependent regions demonstrating higher vulnerability compared to resource-abundant eastern basins. Elasticity analysis indicates that improvements in irrigation efficiency have a substantially greater impact on sustainability than equivalent changes in transboundary inflows, highlighting the dominant role of internal system performance. The findings suggest that water sustainability in Kazakhstan is primarily constrained by governance effectiveness and efficiency limitations rather than absolute resource scarcity. This study contributes to the literature by integrating quantitative hydrological indicators with institutional analysis through a composite modeling framework, demonstrating that internal system efficiency—particularly irrigation performance—has a significantly greater influence on sustainability outcomes than external hydrological variability. The proposed approach provides a transferable methodology for assessing water sustainability in semi-arid and transboundary contexts. Full article

Hydro-cultural heritage is shaped by strong hydrological dependence and historical accessibility. To address insufficient identification of river-basin heritage linkages and their weak translation into graded protection, this study develops an analytical framework integrating heritage-site evaluation, cultural source identification, resistance-surface construction, potential corridor extraction, network grading, and protection guidance, and applies it to the Xiangjiang River Basin, China. Heritage sites were evaluated by protection level, historical continuity, spatial proximity, and hydro-cultural relevance. Cultural source areas were identified using weighted kernel density analysis, potential corridors were extracted using the minimum cumulative resistance model, and the graded corridor network was examined using network-structure indices. The results show river-oriented clustering, localized nucleation, and belt-like extension. Eight primary and fourteen supplementary cultural source areas were identified. Potential corridors are concentrated along the Xiangjiang main stem and major tributaries. In the resistance-surface construction, distance to the water system received the highest AHP-derived resistance weight, while GeoDetector showed that it had the highest, although modest, single-factor explanatory power among the tested variables for corridor spatial differentiation. The corridor network exhibits a primary–secondary–tertiary graded structure. This study reveals the spatial continuity and hierarchy of hydro-cultural heritage corridors and provides a methodological reference for river-basin conservation. Full article

Integrated energy systems (IES) are widely recognized as a key pathway toward carbon neutrality, enabling the coupling and coordinated optimization of electricity, heat, gas, and cooling. This review provides a structured, technology-oriented overview of IES based on a unified five-subsystem framework (production, conversion, transmission, storage, and consumption). It systematically covers: (1) renewable energy utilization—solar, wind, and geothermal—supported by a global spatial distribution map and representative top-performing commercial products; (2) energy cascade utilization, where combined heat and power/combined cooling, heating and power (CHP/CCHP) raises overall efficiency from approximately 35–40% to 70–90%; (3) multi-form energy storage—electrical, electrochemical, chemical, thermal, and mechanical—distinguishing short-term balancing (e.g., lithium-ion (Li-ion), flywheels, supercapacitors, with 85–95% round-trip efficiency) from long-duration and seasonal applications (e.g., pumped hydro, hydrogen/power-to-gas (P2G), redox flow batteries); and (4) forecasting, collaborative optimization, and the bidirectional integration of IES with smart grids and grid modernization. A strategic strengths, weaknesses, opportunities, and threats–Political, Economic, Sociological, Technological, Legal, and Environmental (SWOT–PESTLE) analysis is further presented to position IES within the global energy transition. The review highlights that IES and grid innovation are mutually enabling, and that realizing the full carbon-neutrality potential of IES requires coordinated progress in standardization, digitalization, long-duration storage, and cross-sector policy alignment. Full article

Heap bioleaching is widely used to extract copper from low-grade sulfide ores thanks to its operational simplicity, low cost, and environmental sustainability. However, current control strategies rely primarily on single-factor optimization and often overlook the synergistic interactions of multiple key parameters, such as ore particle size, pore structure, pH, temperature, microbial activity, and oxygen transfer efficiency. As a result, issues such as low recovery rates, extended leaching periods, and high operational costs persist. Moreover, the “gray-box” nature of heap systems impedes real-time monitoring of internal physical, chemical, and biological processes. In addition, empirical multi-parameter optimization is time-consuming and inadequate for capturing complex interdependencies. This review was conducted to systematically examine the key factors influencing heap bioleaching efficiency and critically evaluate recent advances in numerical simulation and intelligent control strategies. As a result, we identified a major research gap: the existing models—including microscale shrinking core models (SCMs), mesoscale pore-network models based on CT reconstruction, and macroscale continuum models—have inherent limitations. SCMs assume idealized spherical particles with uniform mineral distribution while neglecting pore structure evolution and biofilm dynamics. Mesoscale models offer detailed pore characterization but lack robust multi-physics coupling (thermal–hydro–mechanical–chemical–biological, or THMCB). Macroscale models rely on homogenization assumptions that oversimplify spatial heterogeneity and temporal variations in permeability. This analysis covers the relevant literature from 1985 to 2025, with a focus on three methodological scales (micro, meso, and macro) and their integration with machine learning approaches. A notable finding is that hybrid neural network models (e.g., BP and RBF architectures) outperform purely physics-based models in predicting leaching kinetics under varying operational conditions. However, their accuracy depends heavily on high-quality field data—a limitation rarely addressed in prior reviews. By clearly delineating these model-specific limitations and scale-dependent trade-offs, this review makes two unique contributions: a structured framework for selecting and coupling numerical methods according to process requirements and a roadmap for integrating artificial neural networks with multi-physics simulations to achieve real-time intelligent control of heap bioleaching. The findings offer both theoretical guidance and practical references for optimizing the processing of low-grade copper sulfide ores. Full article

Background: Agroecology is increasingly discussed as a strategic response to the combined challenges of drought, ecological degradation, and rural vulnerability. In Morocco, this debate has become particularly urgent because agriculture now operates under persistent hydro-climatic stress, declining water availability, and strong territorial disparities between rainfed, irrigated, mountain, and oasis systems. Methods: This article is based on a structured critical review combined with an interpretive bibliometric synthesis of Moroccan and North African literature on agroecology, water stress, agricultural transition, and food-system resilience. The review was organized through conceptual framing, targeted source selection, thematic screening, and integrative synthesis. Results: Morocco is not an agroecological blank slate. Practices compatible with agroecological transition already exist across the country, including crop diversification, legume rotations, crop–livestock integration, biological regulation, organic amendments, and multifunctional production systems. However, previous reviews have mainly documented practices, projects, or sustainability initiatives without fully explaining why these remain weakly connected, poorly scaled, and insufficiently institutionalized under Moroccan conditions. This review shows that the principal barrier is not the absence of relevant practices but the absence of a coherent transition architecture capable of aligning water governance, farm economics, advisory systems, public incentives, territorial differentiation, and market valorization. The Moroccan case reveals a central paradox: agroecology is most necessary precisely where the structural conditions for its adoption are most fragile. To capture this contradiction, the paper proposes the concept of a Hydro-Agroecological Transition Trap, defined as a condition in which worsening water stress simultaneously intensifies the need for agroecological redesign and reduces the ability of farms and institutions to implement it. Conclusions: The manuscript concludes by proposing a six-pillar transition framework for Morocco based on water-smart agroecology, territorially differentiated pathways, participatory innovation, transition finance and risk-sharing, market construction, and multidimensional assessment. The originality of the study lies in shifting the analysis from a shortage of practices to a shortage of transition architecture, thereby contributing to international debates on agroecological scaling under chronic hydro-climatic stress. Full article

Injection operations are critical in subsurface energy engineering, where wellbores endure complex thermo-hydro-mechanical (THM) coupling under high-temperature and high-pressure conditions, impacting tubing string stability and wellbore long-term safety. Current tubing string THM research relies on simplified assumptions, focusing on single/dual-field coupling without full-scale modeling, failing to accurately characterize comprehensive multi-field behaviors or actual structural stress distributions. This paper presents a full-scale THM coupled numerical model for actual injection conditions, taking real wellbore structures as the object to realize unified modeling of tubing, packer, casing, cement sheath and formation, covering the entire well section and synergistically describing fluid flow, heat conduction and structural mechanical response. It considers fluid pressure/temperature effects on tubing axial load, thermal stress and deformation, as well as nonlinear boundary conditions like packer-casing contact and friction. The governing equations are discretized via the finite element method and solved by Newton iteration. Benchmark verification shows the maximum relative errors of casing inner/outer wall Mises stress vs. analytical solutions are 2.43% and 4.98%, confirming high accuracy. Systematic analysis of displacement, axial force, stress and temperature responses under typical conditions is conducted, providing reliable theoretical and technical support for wellbore structure optimization, injection parameter regulation and long-term wellbore integrity evaluation. Full article

Intensity–Duration–Frequency (IDF) curves are the cornerstone of hydraulic infrastructure design, yet standard methodologies often fail to account for the complex dependence structure of rainfall characteristics and the non-stationary effects of climate change. This study develops a robust Regional Copula Framework for the Kastoria Lake basin, Greece, utilizing sub-hourly rainfall records from four meteorological stations (2007–2024). We employ a forensic data quality control process to pool 277 independent storm events. Unlike traditional approaches, our analysis demonstrates that the Generalized Extreme Value (GEV) distribution (ξ = 0.348) significantly outperforms the standard Lognormal distribution in modeling heavy-tailed rainfall intensities. The dependence between storm duration and intensity was found to be consistently negative (τ = −0.35), a structure best captured by the Rotated Gumbel (90°) copula, which physically reflects the region’s convective storm dynamics. Trend analysis revealed a statistically significant decrease in peak intensity (τ = −0.14) coupled with an increase in storm duration (τ = 0.22), a hydro-climatic shift that contrasts with increasing intensity trends reported in the wider Balkan region. These findings suggest a regime transition from flash-flood dominance to volume-critical events, necessitating updated design criteria that integrate both multivariate dependence and local climatic non-stationarity. Full article

The transition from petrochemical plastics to sustainable biopolymers has created a critical demand for functional materials that do not compromise on performance. Starch and zein, due to their abundance and complementary nature, represent not just a chemical pair, but a techno-economic symbiosis: zein provides the hydrophobic shield, while starch offers the cost-effective structural volume. This review adopts a “Puzzle Theory” framework to synthesize over 80 peer-reviewed studies published between 2014 and 2025, categorizing the literature into established structural knowledge and unresolved functional limitations. Our analysis reveals that while fabrication protocols and molecular synergy are well-defined in approximately 65% of the surveyed literature, critical functional data remain largely absent. Specifically, fewer than 15% of studies investigate hydro-stability in high-humidity environments or bio-interface behavior, creating a disconnect between laboratory success and industrial application. We identify that current research disproportionately prioritizes dry-state morphology over wet-state mechanical integrity. To bridge the gap between academic prototypes and industrial reality, this article moves beyond general recommendations to propose concrete experimental benchmarks, including specific targets for wet mechanical integrity (>1 MPa), regulatory solvent compliance (<50 ppm), and scalable throughput. This article concludes by providing a strategic roadmap to bridge these gaps, arguing that future research must pivot from simple morphological characterization to developing “smart response” mechanisms and “green manufacturing” protocols to ensure commercial viability. Full article

As climate-driven disasters intensify globally, this study investigates how environmental volatility influences the pro-environmental initiatives of micro-entrepreneurs in Chile. While Chile possesses world-class seismic resilience, the 2020–2025 period marked a dramatic shift toward hydro-climatological extremes, including mega-fires and catastrophic flooding. Integrating construal level theory, protection motivation theory, and the concept of focusing events, this research examines the psychological and structural drivers of business adaptation. Results indicate that residing in disaster-prone regions is insufficient to trigger proactivity; instead, a stark distinction exists between abstract geographic proximity and the behavior triggered by personal exposure. Furthermore, mediation analysis provides mixed support for the role of business profit; while profit loss negatively mediated equipment efficiency and recycling, the magnitude was marginal. This coping gap suggests that resource-constrained actors favor low-cost survivalist tactics over systemic shifts due to depleted organizational slack. Ultimately, the study highlights that disasters are powerful but inefficient teachers; without addressing technical and financial barriers to mitigation, global supply chains remain fragile despite localized disaster experiences. Full article

Large-scale river modeling has transitioned toward vector-based routing, yet the global fidelity of standalone frameworks like mizuRoute remains poorly characterized due to fragmented observation networks and unquantified systematic biases. This study addresses this gap by establishing a comprehensive global benchmark using a harmonized database of 12,115 in situ gauging stations integrated with multi-dimensional catchment attributes. Simulations utilize the 5 km MERIT-Hydro network driven by ERA5-Land runoff from 1980 to 2024. Our results reveal a robust global median Pearson correlation of 0.53, though simulation efficiency is highly bifurcated with a median Kling–Gupta Efficiency (KGE) of 0.17. High fidelity is concentrated in humid temperate and cold regions, whereas performance collapses in arid zones (median KGE = −0.15) due to the structural omission of channel transmission losses. Attribution analysis identifies the aridity–moisture gradient and vegetation density as primary drivers of model skill, while topographic complexity is well-preserved by the vector framework. Furthermore, anthropogenic regulation significantly degrades accuracy; in basins with high reservoir density, naturalized routing fails to capture regulated flow signatures, leading to a sharp decline in efficiency. This work provides the first global appraisal of the mizuRoute framework and highlights that integrating dryland-specific loss functions and reservoir modules is essential for the next generation of global hydrological reconstructions. Full article

Addressing the growing need for sustainable innovation in PVC materials, this study presents an illustrative framework that develops and demonstrates an ontological system that integrates lifecycle simulation using Granta EduPack, systematic literature analysis (including bibliometric, thematic, and content analytics) of peer-reviewed publications, and Protégé-based semantic reasoning, and their combination, in a holistic manner. Material and use-phase data for PVC, HDPE, PP, PET, and FRP cooling-tower components were sourced from ANSYS Granta EduPack Level-3 Polymer Sustainability 2023 R2 Version; 23.2.1, and a systematic analysis of the literature was then encoded as ontology classes, properties, and individuals following the Seven-Step ontology development method. Eco-audit simulations, standardised to a functional unit of 1 kg cooling tower fill material, reveal that the use phase dominates environmental impact (67 MJ primary energy, ~80% of total lifecycle), while material production and end-of-life recycling contribute ~15% and credits of ~900 MJ and 28 kg CO₂ via recycling offsets. Ontology reasoning with corrected SWRL rules and SPARQL queries classifies VirginPVCRef and PVC10ES as strong structural materials (tensile strength ≥ 40 MPa), identifies PVCRH40 as high-moisture-risk (water absorption > 0.10 g/g), and ranks hydro-thermal dechlorination (recyclability 0.90) over mechanical recycling (0.55). A systematic analysis of 40 Scopus-indexed publications (2015–2025) highlighted key themes in recycling technologies, LCA emissions, additive toxicity, ontology frameworks, machine learning integration, circular economy policy, and cooling-tower applications. Demonstrated via a simulation-based cooling-tower case study, hybrid PVC-FRP designs yield the highest justified Material Sustainability Performance Index (MSPI), outperforming PVC-only and FRP-only alternatives. This framework provides a conceptual decision-support tool for exploring PVC material optimisation, illustrating pathways to enhancing circularity and environmental responsibility in industrial applications. The proposed framework is, therefore, not intended as a validated decision-support tool, nor does it claim analytical optimisation or predictive performance but rather serves as a method of illustration that shows how domain knowledge can be formally structured using ontology principles linked to simulation representations, and that was examined for internal logical consistency. Full article